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TooT-PLM-P2S

Transformers
PyTorch
t5
text2text-generation
Generated from Trainer
text-generation-inference
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 Community
ghazikhanihamed commited on
Commit
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1 Parent(s): 26b21c2

PLM-Secondary-Structure-Generation

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Files changed (5) hide show
  1. README.md +21 -12
  2. pytorch_model.bin +1 -1
  3. tokenizer.json +16 -2
  4. tokenizer_config.json +2 -1
  5. training_args.bin +1 -1
README.md CHANGED
@@ -15,8 +15,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [ElnaggarLab/ankh-base](https://huggingface.co/ElnaggarLab/ankh-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1736
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- - Q3 Accuracy: 0.5107
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  ## Model description
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@@ -35,27 +35,36 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1e-05
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  - train_batch_size: 1
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  - eval_batch_size: 8
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- - seed: 7
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  - distributed_type: multi-GPU
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- - num_devices: 6
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- - gradient_accumulation_steps: 2
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- - total_train_batch_size: 12
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- - total_eval_batch_size: 48
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.3
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- - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Q3 Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:-----------:|
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- | 0.2839 | 1.0 | 848 | 0.2462 | 0.3434 |
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- | 0.18 | 2.0 | 1696 | 0.1814 | 0.5245 |
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- | 0.1691 | 3.0 | 2544 | 0.1736 | 0.5107 |
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [ElnaggarLab/ankh-base](https://huggingface.co/ElnaggarLab/ankh-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1649
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+ - Q3 Accuracy: 0.5470
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.001
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  - train_batch_size: 1
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  - eval_batch_size: 8
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+ - seed: 42
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  - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 16
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+ - total_eval_batch_size: 32
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.3
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+ - num_epochs: 1
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Q3 Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:-----------:|
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+ | 1.0993 | 0.08 | 50 | 0.3957 | 0.4526 |
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+ | 0.4077 | 0.16 | 100 | 0.3564 | 0.5574 |
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+ | 0.3475 | 0.24 | 150 | 0.3082 | 0.4327 |
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+ | 0.2474 | 0.31 | 200 | 0.2171 | 0.5477 |
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+ | 0.2567 | 0.39 | 250 | 0.3058 | 0.4924 |
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+ | 0.2948 | 0.47 | 300 | 0.1828 | 0.5470 |
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+ | 0.2148 | 0.55 | 350 | 0.1873 | 0.5470 |
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+ | 0.209 | 0.63 | 400 | 0.1832 | 0.5470 |
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+ | 0.1761 | 0.71 | 450 | 0.1791 | 0.5103 |
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+ | 0.1791 | 0.79 | 500 | 0.1700 | 0.5470 |
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+ | 0.1641 | 0.87 | 550 | 0.1684 | 0.5470 |
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+ | 0.1653 | 0.94 | 600 | 0.1649 | 0.5470 |
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  ### Framework versions
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tokenizer_config.json CHANGED
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  "tokenizer_class": "T5Tokenizer",
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